1 Ocak 2002 Dergi makalesi Açık Erişim

Kurugollu, F; Sankur, B; Harmanci, AE

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/96571</identifier>
  <creators>
    <creator>
      <creatorName>Kurugollu, F</creatorName>
      <givenName>F</givenName>
      <familyName>Kurugollu</familyName>
    </creator>
    <creator>
      <creatorName>Sankur, B</creatorName>
      <givenName>B</givenName>
      <familyName>Sankur</familyName>
    </creator>
    <creator>
      <creatorName>Harmanci, AE</creatorName>
      <givenName>AE</givenName>
      <familyName>Harmanci</familyName>
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  <titles>
    <title>Image Segmentation By Relaxation Using Constraint Satisfaction Neural Network</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2002</publicationYear>
  <dates>
    <date dateType="Issued">2002-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/96571</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.81043/aperta.96570</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.81043/aperta.96571</relatedIdentifier>
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  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">The problem of image segmentation using constraint satisfaction neural networks (CSNN) has been considered. Several variations of the CSNN theme have been advanced to improve its performance or to explore new structures. These new segmentation algorithms are based on interplay of additional constraints, of varying the organization of the network or modifying the relaxation scheme. The proposed schemes are tested comparatively on a bank of test images as well as real world images. (C) 2002 Elsevier Science B.V. All rights reserved.</description>
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